2019年1月22日 · CatBoost has several parameters to control verbosity. Those are verbose, silent and logging_level. By default logging is verbose, so you see loss value on every iteration. If you want to see less logging, you need to use one of these parameters. It's not allowed to set two of them simultaneously. silent has two possible values - True and False.

2024年4月3日 · I have been following CatBoost tutorials for CatBoostClassifier and CatBoostRanker and have the following questions: What is the difference between using CatBoostClassifier with loss_function PairLogit and using …

2020年11月24日 · So I was running a Catboost model using Python, which was pretty simple, basically: from catboost import CatBoostClassifier, Pool, cv catboost_model = CatBoostClassifier( cat_features=["

2017年10月30日 · Catboost incremental fit for huge data files. You can train your model incrementally as long as you use CPU and init_model as fit parameters. Here is an example of how to do that:

2022年1月25日 · conclusion:catboost doesn't provide fuctionality to handle missing values in categorical variables. original text: The feature f is categorical and takes the value None for some object Obj. A matrix is used for the training. The column that contains the value of the feature f for the object Obj contains the value None.

2017年12月9日 · Running catboost on a large-ish dataset (~1M rows, 500 columns), I get: Training has stopped (degenerate solution on iteration 0, probably too small l2-regularization, try to increase it).

2021年5月22日 · I am trying to use CatBoost Classifier. Using it I do perform a grid search using randomised_search() method. Unfortunately, the method prints to stdout iteration results for each tree built for each model tried. There is a parameter supposed to control this: verbose.

2025年2月18日 · According to the catboost installation docs CatBoost Python package supports only CPython Python implementation with versions < 3.13. Version 3.13.x support is in progress.

2020年12月27日 · @BenReiniger There is a problem in catboost inner working, for some loop instead of [549 0 342 0] it returns [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 16 90 287 126 30 0 0 5 82 110 129 16 0 0 0 0 0 0] meaning it's not a binary classifier anymore. This is why unpacking fails.

2019年1月15日 · I want to pass 12th column of a numpy array as categorical feature. The column has int values from 1 to 10. I tried this: cbr.fit(X_train, y, eval_set=(X_train_test, y_test),